Fully automated natural frequency identification based on deep-learning-enhanced computer vision and power spectral density transmissibility
Autor(en): |
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) |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Advances in Structural Engineering, Juni 2022, n. 13, v. 25 |
Seite(n): | 136943322211075 |
DOI: | 10.1177/13694332221107572 |
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Datenseite - Reference-ID
10678383 - Veröffentlicht am:
18.06.2022 - Geändert am:
19.04.2023