Crack Identification for Bridge Condition Monitoring Combining Graph Attention Networks and Convolutional Neural Networks

Crack Identification for Bridge Condition Monitoring Combining Graph Attention Networks and Convolutional Neural Networks

Orthotropic steel box girders and steel bridge decks are commonly applied to bridges. Because of the coupling of original defects and alternating forces, fatigue cracks are likely to appear in the structures. In order to ensure the life span of bridges, methods for automatic crack identification are...

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Bibliographic Details
Main Authors: Feiyu Chen, Tong Tong, Jiadong Hua, Chun Cui
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
crack identification
convolutional neural networks
graph attention networks
machine vision
bridge condition monitoring
Online Access:https://www.mdpi.com/2076-3417/15/10/5452
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