基本信息
姓名:李生元
出生年月:1990年7月
学位:博士
职称:讲师
研究领域:土木工程结构损伤智能诊断、计算机视觉算法开发与应用、新型结构健康监测传感器研发
招收研究生专业:结构工程、防灾减灾工程及防护工程
E-mail: lisy@cumt.edu.cn
个人简介
李生元,男,甘肃武威人。2020年博士毕业于大连理工大学结构工程专业,主要从事土木工程结构损伤智能诊断、计算机视觉算法开发与应用、新型结构健康监测传感器研发等研究。主持国家自然科学基金青年基金项目1项,中国博士后科学基金面上资助1项,省部级项目1项,参与国家重点研发计划项目1项,参与企事业单位委托科技项目多项。在Computer-Aided Civil and Infrastructure Engineering、Automation in Construction等期刊和国际会议发表学术论文20余篇,其中ESI热点、高被引论文各1篇。获国家授权发明专利2项,参编专著1部。担任Automation in Construction、Measurement等多个国际国内期刊审稿人。
教育经历
2016.9-2020.12,大连理工大学,结构工程,博士,导师:赵雪峰
2014.9-2016.6,大连理工大学,建筑与土木工程,硕士,导师:赵雪峰
2010.9-2014.6,兰州理工大学,土木工程,本科
科研、学术与访学工作经历
2021.1-至今,中国矿业大学,澳门太阳集团城9728,讲师
主持或参与科研项目及人才计划项目情况
纵向:
1.国家自然科学基金青年科学基金项目,52308333,数据驱动的海洋环境下RC桥墩表面损伤三维识别与演化规律研究,2024/1-2026/12,30万元,在研,主持。
2.中国博士后科学基金面上资助二等,22M723401,2022/9-2023/12,8万元,在研,主持。
3.江苏建筑节能与建造技术协同创新中心开放基金,SJXTBH02,煤矿环境与荷载耦合作用下钢筋混凝土结构智能检测与鉴定加固研究,2021/10-2023/10,10万元,在研,主持。
4.中央高校基本科研业务费专项青年科技基金,2021QN1021,基于深度学习的混凝土结构表面损伤检测技术,2021/1-2022/12,6万元,已结题,主持。
5.国家重点研发计划,2016YFE0202400,高寒地区公路设施全寿命周期耐久性提升与安全性保障关键技术子课题,2017/9-2020/8,555万元,已结题,参与。
代表性研究成果和学术奖励情况
一、代表性论文
1. Li Shengyuan, Zhao Xuefeng, Zhou Guangyi. Automatic pixel-level multiple damage detection of concrete structure using fully convolutional network[J]. Computer-Aided Civil and Infrastructure Engineering, 2019, 34(7): 616-634. (SCI, ESI热点、高被引论文)
2. Li Shengyuan, Zhao Xuefeng. Image-based concrete crack detection using convolutional neural network and exhaustive search technique[J]. Advances in Civil Engineering, 2019, 2019: 6520620. (SCI, ESI高被引论文)
3. Li Shengyuan, Zhao Xuefeng. High-resolution concrete damage image synthesis using conditional generative adversarial network[J]. Automation in Construction, 2023, 147: 104739. (SCI, Top期刊)
4. Li Shengyuan, Lv Henglin, Huang Tianhua, Zhang Zhigang, Yao Jin, Ni Xin. Degradation of reinforced concrete beams subjected to sustained loading and multi-environmental factors[J]. Buildings, 2022, 12(9): 1382. (SCI)
5. Li Shengyuan, Zhao Xuefeng. A performance improvement strategy for concrete damage detection using stacking ensemble learning of multiple semantic segmentation networks[J]. Sensors, 2022, 22(9): 3341. (SCI)
6. Li Shengyuan, Zhao Xuefeng. Pixel-level detection and measurement of concrete crack using faster region-based convolutional neural network and morphological feature extraction[J]. Measurement Science and Technology, 2021, 32(6): 065010. (SCI)
7. Li Shengyuan, Zhao Xuefeng. Automatic crack detection and measurement of concrete structure using convolutional encoder-decoder network[J]. IEEE Access, 2020, 8: 134602-134618. (SCI)
8. Li Shengyuan, Lv Haifeng, Kuang Yachuan, Deng Nianchun, Sun Changsen, Zhao Xuefeng. Force-monitoring ring based on white-light interferometry for bridge cable force monitoring and its temperature compensation[J]. Advances in Structural Engineering. 2019, 22(6): 1444-1452. (SCI)
9. Li Shengyuan, Zhao Xuefeng. Convolutional neural networks-based crack detection for real concrete surface[C]// SPIE Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018, 2018, 10598: 105983V. (EI)
10. Li Shengyuan, Li Peigang, Zhang Yang, Zhao Xuefeng. Detection of component types and track damage for high-speed railway using region-based convolutional neural networks[C]// ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, 2018. (EI)
11. Zhao Xuefeng, Li Shengyuan, Su Hongguo, Zhou Lei, Loh Kenneth. Image-based comprehensive maintenance and inspection method for bridges using deep learning[C]// ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, 2018. (EI)
12. Zhao Xuefeng, Li Shengyuan. A method of crack detection based on convolutional neural networks[C]// 11th International Workshop on Structural Health Monitoring 2017, 2017, 1: 978-984. (EI,ResearchGate阅读量已达7600余次)
13.赵雪峰,李生元,欧进萍.基于人工智能与智能手机的混凝土裂纹检测[J].物联网技术, 2017, 7(8): 15-18.
二、发明专利
[1]一种光纤拉索预应力监测方法及其传感器,发明专利号:ZL201410849987.4, 2017.2.1. (排名4/5)
[2]一种适用于不同直径光纤线圈制作的光纤缠绕机,发明专利号:ZL201410836015.1, 2017.1.11. (排名2/4)
三.专著及教材
1.赵雪峰等.结构智能手机云监测[M].北京:科学出版社, 2021/11.参编。