林威

职称:副教授

通讯地址:福建省福州市福州大学城乌龙江北大道2号 福州大学土木工程学院南103室

邮政编码:350108

Email:linwei0763@fzu.edu.cn

个人简介

林威,福建莆田人,工学博士,毕业于同济大学(剑桥大学联合培养),现任福州大学土木工程学院智能建造系副教授,福建省2025届引进生。主要从事地下基础设施智能建造与维养相关研究,研究方向涵盖三维激光扫描、计算机视觉、深度学习、数字孪生、结构性能评估等。参与国家重点研发计划课题与国家自然科学基金重点项目等国家级研究课题多项,发表论文27篇,申请或授权发明专利11项。

将心比心,亦师亦友,尊重学生发展意愿,为学生进步提供良好条件。(招生专业:081401岩土工程学硕、085901土木工程专硕)

个人主页:https://linwei0763.github.io/

谷歌学术:https://scholar.google.com/citations?user=sqagIuoAAAAJ

教育经历

2021.03–2025.09,同济大学,土木工程,博士研究生(导师:谢雄耀 教授)

2023.04–2024.03,剑桥大学,土木工程,访问博士研究生(导师:Brian Sheil 副教授)

2019.09–2021.02,同济大学,建筑与土木工程,硕士研究生(导师:谢雄耀 教授)

2015.09–2019.07,同济大学,土木工程,本科

荣誉奖励

1. 2026.01,TUST Best Paper Awards 2024

2. 2024.05,GeoShanghai Prize for Service Award

3. 2022.07,国家留学基金管理委员会奖学金

4. 2021.12,工程建设科学技术进步奖,二等奖

5. 2021.09,“张江国信安杯”BIM建模大赛,三等奖

6. 2021.01,同济大学优秀学生

7. 2019.05,上海市优秀毕业生

8. 2019.01,同济大学优秀学生

9. 2018.12,同济大学优秀学生奖学金,二等奖

10. 2018.03,同济大学优秀学生

11. 2017.11,国家奖学金

12. 2017.06,全国周培源大学生力学竞赛,二等奖

13. 2016.12,同济大学优秀学生奖学金,一等奖

14. 2015.08,许阿琼奖学金

学术成果

英文期刊论文

1. Guan, Z., Liu, Y., Lin, Y., & Lin, W.* (2026). Accurate measurement of segment dislocation for shield tunnel based on binocular vision technology. Journal of Computing in Civil Engineering, 40(3), 04026004. (中科院二区, JCR Q1)

2. Lin, W., Sheil, B., Zhang, P., Chang, J., & Xie, X.* (2025). Automated digital reconstruction of high-fidelity present-day geometries for segmental tunnel linings based on segmented point clouds. Tunnelling and Underground Space Technology, 164, 106859. (中科院一区TOP, JCR Q1)

3. Lin, W., Sheil, B., Zhang, P., Li, K., & Xie, X.* (2025). Structural geometry-informed 3D deep learning for segmental tunnel lining analysis in point clouds. Automation in Construction, 176, 106281. (中科院一区TOP, JCR Q1)

4. Lin, W., Zou, M., Zhao, M., Chang, J., & Xie, X.* (2025). Multi-fidelity machine learning for identifying thermal insulation integrity of liquefied natural gas storage tanks. Applied Sciences, 15, 33. (中科院三区, JCR Q1)

5. Lin, W., Sheil, B., Zhang, P., Zhou, B., Wang, C., & Xie, X.* (2024). Seg2Tunnel: A hierarchical point cloud dataset and benchmarks for segmentation of segmental tunnel linings. Tunnelling and Underground Space Technology, 147, 105735. (中科院一区TOP, JCR Q1)

6. Lin, W., Li, P.*, Xie, X., Cao, Y., & Zhang, Y. (2023). A novel back-analysis approach for the external loads on shield tunnel lining in service based on monitored deformation. Structural Control and Health Monitoring, 2023, 8128701. (中科院二区, JCR Q1)

7. Lin, W., Li, P.*, & Xie, X. (2022). A novel detection and assessment method for operational defects of pipe jacking tunnel based on 3D longitudinal deformation curve: A case study. Sensors, 22, 7648. (中科院二区, JCR Q2)

8. Zhang, R., Lin, W., Wang, C., Sheil, B., Liu, Z., & Li, Z.* (2026). Denoising image point clouds using segmentation and synthetic data for enhanced structural health analysis of tunnels. Data-Centric Engineering, 7, e10. (中科院三区, JCR Q2)

9. Jing, Y.*, Lin, W., Sheil, B., & Acikgoz, S. (2025). 3D multimodal feature for infrastructure anomaly detection. Automation in Construction, 178, 106388. (中科院一区TOP, JCR Q1)

10. Huang, H., Chang, J.*, Zhang, D., Thewes, M., & Lin, W. (2025). Improved model-free adaptive control of shield machine posture during tunnelling. Advanced Engineering Informatics, 67, 103465. (中科院一区TOP, JCR Q1)

11. Ye, Z., Lin, W., Faramarzi, A., Xie, X., & Ninić, J.* (2025). SAM4Tun: No-training model for tunnel lining point cloud component segmentation. Tunnelling and Underground Space Technology, 158, 106401. (中科院一区TOP, JCR Q1)

12. Chang, J., Thewes, M., Zhang, D., Huang, H.*, & Lin, W. (2025). Deformational behaviors of existing three-line tunnels induced by under-crossing of three-line mechanized tunnels: A case study. Canadian Geotechnical Journal, 62, 23. (中科院三区, JCR Q2, ESI高被引论文)

13. Li, K., Xie, X., Zhou, B.*, Huang, C., Lin, W., Zhou, Y., & Wang, C. (2024). Thickness regression for backfill grouting of shield tunnels based on GPR data and CatBoost & BO-TPE: A full-scale model test study. Underground Space, 17, 100–119. (中科院一区, JCR Q1)

中文期刊论文

1. 吴庆杰, 张红伟, 陈少林, & 林威*. (2025). 基于计算机视觉的盾构隧道管片错台自动测量方法. 施工技术(中英文), 54(17), 40–44.

2. 林威, 谢雄耀*, 关振长, & 常佳奇. (2025). 基于改进标签编码和RandLA-Net的盾构隧道点云逐管片自动分割和变形提取算法. 中国公路学报. (EI, CSCD, 北大核心)

3. 张洋宾, 谢雄耀*, 周彪, 林威, 曹宇阳, 张列学, & 王承. (2025). 基于关联规则的盾构隧道结构性能评价方法. 同济大学学报(自然科学版), 53(6), 888–897. (EI, CSCD, 北大核心)

4. 石州, 谢雄耀*, 曾昆, 卜祥波, 林威, & 徐子龙. (2025). 考虑过程响应的盾构隧道施工管片变形研究. 土木与环境工程学报(中英文), 47(5), 155–166. (北大核心)

5. 邹成路, 林威, 罗文静, 周彪*, & 谢雄耀. (2022). 城市轨道交通车站半成岩深基坑围护结构变形特性研究. 城市轨道交通研究, 25(3), 150–155. (北大核心)

6. 谢雄耀, 林威, 周彪*, & 邹成路. (2022). 半成岩超深基坑围护结构变形与受力特性研究. 结构工程师, 38(1), 164–172.

7. 梁小波, 林威, 徐金峰, 刘志义, & 赵刚. (2022). 滇中红层软岩填料高路堤稳定性分析. 建筑施工, 44(9), 2248–2251.

会议论文

1. Lin, W., Sheil, B., Xie, X.*, Zhang, Y., & Cao, Y. (2024). Semantic segmentation of large-scale segmental lining point clouds using 3D deep learning. GeoShanghai International Conference 2024, 012026. (CPCI-S)

2. Lin, W.*, Sheil, B., Xie, X., Li, K., & Niu, G. (2024). Segment segmentation of tunnel ring point clouds using 3D deep learning. World Tunnel Congress 2024, 3059–3066. (EI)

3. Lin, W., Xie, X., Zhou, B., Li, P., & Wang, C. (2023). Refined perception and management of ring-wise deformation information for shield tunnels based on point cloud deep learning and BIM. Eighth International Symposium on Life-Cycle Civil Engineering (IALCCE 2023), 3991–3998. (EI)

4. Lin, W., Xie, X.*, Li, P., Xiao, B., Lu, X., Feng, B., Jin, P., & Hu, Y. (2022). Prediction of settlement induced by tidal fluctuation for underwater shield tunnel during service based on historical monitoring data. 2022 8th International Conference on Hydraulic and Civil Engineering: Deep Space Intelligent Development and Utilization Forum (ICHCE), 1042–1047. (EI, CPCI-S)

5. Ye, Z., Faramarzi, A., Ninić, J., & Lin, W. (2025). Automated digital twin reconstruction for tunnel inspection and maintenance. World Tunnel Congress 2025, 517–524. (EI)

6. Cao, Y., Xie, X., Zhou, B., Lin, W., Zhang, Y., & Tang, G. (2025). Effect of the crossing super-large-diameter shield tunnel construction on ground surface settlement. World Tunnel Congress 2025, 2029–2036. (EI)

7. Zhang, Y., Xie, X., Lin, W., Cao, Y., & Tang, G. (2025). Electric power tunnel maintenance strategy based on structural performance chained evolutionary networks. World Tunnel Congress 2025, 4343–4349. (EI)

专利

1. 林威, 关振长, 徐诗涵, 黄一韩, 林志城, & 许辉. (2026). 一种基于深度学习的山岭隧道开挖面渗漏水定量监测方法 (Patent No. CN202512026457.0). (发明申请)

2. 林威, 关振长, 徐诗涵, 黄一韩, 林志城, & 许辉. (2026). 一种融合激光和视频数据的山岭隧道渗漏水实时监测方法 (Patent No. CN202511733577.8). (发明申请)

3. 李向瑞, 关振长, 孙远方, 林威, 宋成年, 何敬房, & 黄正业. (2026). 一种钻爆法隧道施工质量评估方法及系统 (Patent No. CN202511832090.5). (发明授权)

4. 李向瑞, 关振长, 孙远方, 林威, 宋成年, 何敬房, & 黄正业. (2026). 一种基于相关算法和数据融合的山岭隧道开挖面变形区域识别方法 (Patent No. CN202511732842.0). (发明申请)

5. 施静康, 魏成凯, 关振长, 林威, 骆剑彬, & 张鹤. (2026). 一种高灵敏度RFID贴片天线式应变传感器 (Patent No. CN202511598773.9). (发明申请)

6. 施静康, 周博涵, 关振长, 林威, 骆剑彬, & 张鹤. (2026). 一种基于改进的UNet探地雷达电导率和相对介电常数反演方法 (Patent No. CN202511479262.5). (发明申请)

7. 陈洪胜, 谢攀, 朱悦铭, 林威, 谢雄耀, & 唐亘跻. (2025). 基坑土体参数不确定性反演的神经网络方法及计算机系统 (Patent CN202510825034.2). (发明申请)

8. 谢雄耀, 林威, & 唐亘跻. (2025). 一种用于隧道三维点云智能处理的神经网络构建装置及方法 (Patent CN202510484006.9). (发明申请)

9. 牛刚, 秦宝军, 周志广, 肖中林, 杨庆, 孙斌, 邓魏彬, 王亮, 马俊雨, 林威, 周彪, & 谢雄耀. (2025). 一种基于点云特征深度学习的盾构隧道单环点云分割方法 (Patent CN202411358578.4). (发明申请)

10. 周应新, 谢雄耀, 周彪, 林威, 张洋宾, 陈思晗, 徐泓睿, 钱正富, 曾维成, 杨俊宏, 唐能, 刘志义, 史明梅, 唐忠林, 胡兴云, 赵刚, & 叶朋果. (2022). 一种用于差异沉降控制的路堤水载预压反馈调节系统 (Patent CN202211150097.5). (发明申请)

11. 鲁正, 常佳奇, 林威, & 宰秋锐. (2018). 可变阻尼铅芯橡胶阻尼器 (Patent CN201720597425.4). (发明授权)

12. 鲁正, 林威, 常佳奇, & 宰秋锐. (2018). 装配式建筑墙梁节点 (Patent CN201720597493.0). (实用新型授权)

13. 鲁正, 宰秋锐, 常佳奇, & 林威. (2018). 钢结构装配式建筑墙板节点 (Patent CN201720597425.4). (实用新型授权)

学术活动

学术汇报

1. Full-field deformation measurement of shield tunnels using point clouds and deep learning,11th International Conference on Innovative Production and Construction (IPC2025),南昌,2025.08.07

2. Semantic segmentation of large-scale segmental lining point clouds using 3D deep learning,GeoShanghai International Conference 2024,上海,2024.05.27

3. Computer vision for the segmentation of tunnel point clouds: Dataset and network,World Tunnel Congress 2024,深圳,2024.04.24

4. Understanding tunnel point clouds using 3D deep learning, Norwegian Geotechnical Institute,线上,2023.11.01

5. Refined perception and management of ring-wise deformation for segmental linings using 3D deep learning and BIM,Eighth International Symposium on Life-Cycle Civil Engineering (IALCCE 2023),米兰,2023.07.04

6. The digital twin of shield tunnels for structural analysis,hyperTunnel,线上,2023.05.05

7. The digital twin of shield tunnels for structural analysis,Mott MacDonald,线上,2023.04.27

8. AI赋能土木工程科研转型——以计算机视觉为例,福建理工大学第七届土木工程研究生学术论坛,福州,2025.12.07

9. 盾构隧道全空间结构变形智能感知,2025年隧道与地下工程大会暨中国土木工程学会隧道及地下工程分会第25届年会,合肥,2025.10.26

10. 用于大规模盾构隧道点云自动处理的计算机视觉技术,上海市城市建设设计研究总院(集团)有限公司,上海,2024.07.22

会议海报

1. Revealing high-fidelity and present-day geometry of segmental linings by AI,11th International Symposium of Geotechnical Aspects of Underground Construction in Soft Ground (IS-Macau 2024),澳门,2024.06.14–17

2. Prediction of settlement induced by tidal fluctuation for underwater shield tunnel during service based on historical monitoring data,2022 8th International Conference on Hydraulic and Civil Engineering: Deep Space Intelligent Development and Utilization Forum (ICHCE),西安,2022.11.25–27

期刊评审

1. Advanced Engineering Informatics

2. Journal of Computing in Civil Engineering

3. Measurement

4. Automation in Construction

5. International Journal of Digital Earth

6. Tunnelling and Underground Space Technology

7. Underground Space

8. Scientific Reports

研究课题

主持

1. 国家留学基金管理委员会,国家建设高水平大学公派研究生项目[202206260174],Mechanical evaluation and analysis based on digital twin for as-built shield tunnel,2023.04–2024.03

2. 上海市教育委员会,上海市大学生创新创业训练计划项目[201710247118],橡胶支座在装配式建筑墙板节点处的应用,2017.01–2018.01

主要参与

1. 中华人民共和国科学技术部,国家重点研发计划课题[2023YFC3806705],城市大型地下基础设施智能暗挖建造云平台与关键技术应用示范

2. 国家自然科学基金委员会,重点项目[52038008],城市复杂网络化盾构隧道结构前摄性服役保障理论与方法

3. 国家自然科学基金委员会,面上项目[52378408],盾构隧道InSAR沉降感知映射机制及机器学习预警模型

4. 国家自然科学基金委员会,面上项目[51978431],软土盾构隧道前摄性维养模型研究

5. 上海市科学技术委员会,科技创新行动计划[22DZ1203004],超长地下快速路空地融合智能规划及精准测试技术研究