张弛导师简介

一、个人基本信息

姓名：张弛

出生年月：1992年8月

籍贯：湖北省仙桃市

性别：男

民族：汉

职称：讲师

政治面貌：中共党员

最高学历：博士研究生

工作单位：中国民航大学交通科学与工程学院

通讯地址：天津市东丽区津北公路2898号

邮政编码：300300

办公电话：

电子邮箱：chizhang@cauc.edu.cn

二、学习和工作经历

2023.02-今 中国民航大学 交通科学与工程学院 机场系 讲师

2018.09-2023.01 天津大学 建筑工程学院 桥梁与隧道工程专业 获博士学位

三、主要研究方向

结构健康监测与损伤识别，智慧机场

四、学术兼职

五、著作和论文目录

[1] Zhu Jinsong, Zhang Chi, Qi Haidong, et al. Vision-based defects detection for bridges using transfer learning and convolutional neural networks[J]. Structure and Infrastructure Engineering, 2020, 16(7):1037-1049.

[2] Zhu Jinsong, Zhang Chi, Lu Ziyue, et al. A multi-resolution deep feature framework for dynamic displacement measurement of bridges using vision-based tracking system[J]. Measurement: Journal of the International Measurement Confederation, 2021, 183:109847.

[3] Zhang Chi, Zhu Jinsong, Shi Teng. et al. Influence line estimation of bridge based on Elastic Net and vehicle-induced response[J]. Measurement: Journal of the International Measurement Confederation, 2022, 202:111883.

[4] Zhu Jinsong, Zhang Chi, Li Xingtian. Bridge damage detection under moving loads with displacement influence line of a single sensor[J]. Measurement: Journal of the International Measurement Confederation, 2023, 211:112599.

[5] Zhang Chi, Zhu Jinsong, Zhou Shuai, Integration of multi-point influence line information for damage localization of bridge structures[J]. Journal of Civil Structural Health Monitoring, 2023, 已回复二审意见.

[6] Zhu Jinsong, Lu Ziyue, Zhang Chi. A marker-free method for structural dynamic displacement measurement based on optical flow[J]. Structure and Infrastructure Engineering, 2021, 18(1):84-96.

[7] Zhu Jinsong, Li Xingtian, Zhang Chi, et al. An accurate approach for obtaining spatiotemporal information of vehicle loads on bridges based on 3D bounding box reconstruction with computer vision[J]. Measurement: Journal of the International Measurement Confederation, 2021, 181:109657.

[8] Zhu Jinsong, Li Xingtian, Zhang Chi. Fine-grained identification of vehicle loads on bridges based on computer vision[J]. Journal of Civil Structural Health Monitoring, 2022(12): 427–446.