Deep reference autoencoder convolutional neural network for damage identification in parallel steel wire cables

This paper addresses the challenge of overcoming the limited availability of training samples for the damage state of parallel steel wire cables in practical engineering and the difficulty of detecting minor damages. To tackle this issue, we propose an unsupervised deep learning damage identificatio...

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Bibliographic Details

Published in:	Structures (Oxford) Vol. 57; p. 105316
Main Authors:	Xue, Songling, Sun, Yidan, Su, Teng, Zhao, Xiaoqing
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2023
Subjects:	Damage identification DRACNN Parallel steel wire cable Unsupervised deep learning Unsupervised deep learning Parallel steel wire cable Damage identification DRACNN
ISSN:	2352-0124, 2352-0124
Online Access:	Get full text
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