Damage identification method of prestressed concrete beam bridge based on convolutional neural network-Reference-Cited by-同舟云学术

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Damage identification method of prestressed concrete beam bridge based on convolutional neural network

Published:2020-07-23 Issue:2 Volume:33 Page:535-545
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Yang Sanqiang,Huang Yong

Funder

Natural Science Foundation of Hebei Province

Hebei Province High-level Talents Funding Project

Department of science and technology, Ministry of transport

Department of international cooperation, Ministry of science and technology

Hebei Provincial Department of transportation

Xinjiang Uygur Autonomous Region Fund Committee

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-020-05052-w.pdf

Reference31 articles.

1. Zhao Z, Chen C (2002) A fuzzy system for concrete bridge damage diagnosis. Comput Struct 80(7):629–641

2. Banerjee S, Shinozuka M (2008) Mechanistic quantification of RC bridge damage states under earthquake through fragility analysis. Probab Eng Mech 23(1):12–22

3. Kaloop MR, Li H (2011) Sensitivity and analysis GPS signals based bridge damage using GPS observations and wavelet transform. Measurement 44(5):927–937

4. Silva M, Santos A, Figueiredo E et al (2016) A novel unsupervised approach based on a genetic algorithm for structural damage detection in bridges. Eng Appl Artif Intell 52(C):168–180

5. Dziedziech K, Pieczonka L, Kijanka P et al (2016) Enhanced nonlinear crack-wave interactions for structural damage detection based on guided ultrasonic waves. Struct Control Health Monit 23(8):1108–1120

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