Please using THIS link for running the code: https://drive.google.com/drive/u/3/folders/1ijkrKgoohckDMuDRatF9PGHt39jS7t18
Condition Assessment of Stay Cables through Enhanced Time Series Classification Using a Deep Learning Approach
Zhiming Zhang (Louisiana State University), Jin Yan (Iowa State University), Liangding Li (University of Central Florida), Hong Pan ( North Dakota State University), and Chuanzhi Dong (University of Central Florida)
This work wins the first prize of the 1st International Project Competition Structural Health Monitoring (IPC-SHM, 2020) http://www.schm.org.cn/#/IPC-SHM,2020/
The full data used in the code can be requested by contacting the first author at [email protected]. The presentation video has been uploaded to my Youtube channel https://www.youtube.com/channel/UChnhsh0Gtu7SFJAEd3GimrA. The paper can be found on https://arxiv.org/abs/2101.03701.
The LSTM-FCN code for time series classification on https://github.com/titu1994/LSTM-FCN is used for bridge cable condition monitoring in this work.
Please using THIS link for running the code: https://drive.google.com/drive/u/3/folders/1ijkrKgoohckDMuDRatF9PGHt39jS7t18