scholarly journals A hierarchical deep convolutional neural network and gated recurrent unit framework for structural damage detection

2020 ◽  
Vol 540 ◽  
pp. 117-130 ◽  
Author(s):  
Jianxi Yang ◽  
Likai Zhang ◽  
Cen Chen ◽  
Yangfan Li ◽  
Ren Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Damage Detection ◽  
Convolutional Neural Network ◽  
Structural Damage ◽  
Deep Convolutional Neural Network ◽  
Structural Damage Detection ◽  
Gated Recurrent Unit

Structural Damage Detection using Deep Convolutional Neural Network and Transfer Learning

2019 ◽  
Vol 23 (10) ◽  
pp. 4493-4502 ◽  
Author(s):  
Chuncheng Feng ◽  
Hua Zhang ◽  
Shuang Wang ◽  
Yonglong Li ◽  
Haoran Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Damage Detection ◽  
Convolutional Neural Network ◽  
Transfer Learning ◽  
Structural Damage ◽  
Deep Convolutional Neural Network ◽  
Structural Damage Detection

Structural Damage Detection Using Parameters Combined with Changes in Flexibility Based on BP Neural Networks

2011 ◽  
Vol 243-249 ◽  
pp. 5475-5480
Author(s):  
Zhang Jun
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Damage Detection ◽  
Bp Neural Network ◽  
Structural Damage ◽  
The State ◽  
Structural Damage Detection ◽  
Bp Neural Networks ◽  
Simply Supported ◽  
Modal Flexibility

Modals of BP neural networks with different inputs and outputs are presented for different damage detecting schemes. To identify locations of structural damages, the regular vectors of changes in modal flexibility are looked on as inputs of the networks, and the state of localized damage are as outputs. To identify extents of structural damage, parameters combined with changes in flexibility and the square changes in frequency are as inputs of the networks, and the state of damage extents are as outputs. Examples of a simply supported beam and a plate show that the BP neural network modal can detect damage of structures in quantitative terms.

Structural Damage Detection Using an Iterative Neural Network

2000 ◽  
Vol 11 (1) ◽  
pp. 32-42 ◽  
Author(s):  
C. C. Chang ◽  
T. Y. P. Chang ◽  
Y. G. Xu ◽  
M. L. Wang
Keyword(s):  
Neural Network ◽  
Damage Detection ◽  
Structural Damage ◽  
Structural Damage Detection

scholarly journals Embedded system for road damage detection by deep convolutional neural network

2019 ◽  
Vol 16 (6) ◽  
pp. 7982-7994
Author(s):  
Siyu Chen ◽  
◽  
Yin Zhang ◽  
Yuhang Zhang ◽  
Jiajia Yu ◽  
...  
Keyword(s):  
Neural Network ◽  
Embedded System ◽  
Damage Detection ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network
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