Damage Detection in Steel Beams Using Generalized Flexibility Quotient Difference Based Damage Index and Artificial Neural Network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Microbiology (medical),Immunology,Immunology and Allergy
Link
https://link.springer.com/content/pdf/10.1007/s42417-023-01009-0.pdf
Reference44 articles.
1. Nick H, Aziminejad A, Hosseini MH, Laknejadi K (2021) Damage identification in steel girder bridges using modal strain energy-based damage index method and artificial neural network. Eng Fail Anal 119:105010. https://doi.org/10.1016/j.engfailanal.2020.105010
2. Sadeghi F, Yang Y, Zhu X, Li J (2021) Damage identification of steel-concrete composite beams based on modal strain energy changes through general regression neural network. Eng Struct 244:112824. https://doi.org/10.1016/j.engstruct.2021.112824
3. Liu H, Song G, Jiao Y, Zhang P, Wang X (2014) Damage identification of bridge based on modal flexibility and neural network improved by particle swarm optimization. Math probl Eng 2014:640925. https://doi.org/10.1155/2014/640925
4. Tran-Ngoc H, Khatir S, De Roeck G, Bui-Tien T, WahabM A (2019) An efficient artificial neural network for damage detection in bridges and beam-like structures by improving training parameters using cuckoo search algorithm. Eng Struct 199:109637. https://doi.org/10.1016/j.engstruct.2019.109637
5. Kao CY, Hung S-L (2003) Detection of structural damage via free vibration responses generated by approximating artificial neural networks. Comput Struct 81:2631–2644. https://doi.org/10.1016/S0045-7949(03)00323-7
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