Fully automated natural frequency identification based on deep-learning-enhanced computer vision and power spectral density transmissibility
| Auteur(s): |
Zhi-Wei Chen
(Department of Civil Engineering, Xiamen University, Xiamen, China)
Xu-Zhi Ruan (Department of Civil Engineering, Xiamen University, Xiamen, China) Kui-Ming Liu (Department of Civil Engineering, Xiamen University, Xiamen, China) Wang-Ji Yan (State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau, Macau, China) Jian-Tao Liu
(Department of Civil Engineering, Xiamen University, Xiamen, China)
Dai-Cheng Ye (Xiamen Municipal Baicheng Construction & Investment Co. Ltd, Xiamen, China) |
|---|---|
| Médium: | article de revue |
| Langue(s): | anglais |
| Publié dans: | Advances in Structural Engineering, juin 2022, n. 13, v. 25 |
| Page(s): | 136943322211075 |
| DOI: | 10.1177/13694332221107572 |
- Informations
sur cette fiche - Reference-ID
10678383 - Publié(e) le:
18.06.2022 - Modifié(e) le:
19.04.2023
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