Joint damage detection of structures with noisy data by an effective deep learning framework using autoencoder-convolutional gated recurrent unit

Recent advances in chip and sensor technology allow a large amount of data to be collected for serving structural damage detection (SDD). However, how to efficiently utilize and transform these complex sensing data into useful engineering information has remained many challenges. One of the major ch...

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Bibliographic Details

Published in:	Ocean engineering Vol. 243; p. 110142
Main Authors:	Truong, Tam T., Lee, Jaehong, Nguyen-Thoi, T.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.01.2022
Subjects:	Autoencoder-convolutional gated recurrent unit (A-CGRU) Frame structures Noisy data Structural joint damage detection Autoencoder-convolutional gated recurrent unit (A-CGRU) Frame structures Structural joint damage detection Noisy data
ISSN:	0029-8018, 1873-5258
Online Access:	Get full text
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