Chapter
Aug 12, 2020
Multi-Stage Damage Identification Method Based on Integrated Neural Network
Authors: Ya-Xun Yang [email protected], Hai-Bo Yu [email protected], Wen-Hao Chai [email protected], and Fu-Li Yang [email protected]Author Affiliations
Publication: CICTP 2020
ABSTRACT
During the operation of the bridge structure, various structural damages occur due to the sophisticated loads. Failure to detect and handle bridge structure damage opportunely may cause serious accidents. In general, the use of a single type of neural network to identify bridge structural damage has its limitations. Therefore, establish the finite element model of a three-span continuous beam bridge structure and analyze the dynamic characteristics. The process of damage identification is divided into three stages which could reduce the problem difficulty. The input parameters of the neural network damage identification are improved in stages, and several neural networks are integrated at each stage. The final identification results show that the method can effectively identify the damage of bridge structures.
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Published In
CICTP 2020
Pages: 1675 - 1684
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Aug 12, 2020
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1School of Highway, Chang’an Univ., Shaanxi, Xi’an 710064, China. Email: [email protected]
2School of Highway, Chang’an Univ., Shaanxi, Xi’an 710064, China. Email: [email protected]
3School of Highway, Chang’an Univ., Shaanxi, Xi’an 710064, China. Email: [email protected]
4School of Highway, Chang’an Univ., Shaanxi, Xi’an 710064, China. Email: [email protected]
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.