Deep residual network framework for structural health monitoring

Deep residual network framework for structural health monitoring

Convolutional neural networks have been widely employed for structural health monitoring and damage identification. The convolutional neural network is currently considered as the state-of-the-art method for structural damage identification due to its capabilities of efficient and robust feature lea...

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Bibliographic Details
Main Authors: Wang, Ruhua, Chencho, An, Senjian, Li, Jun, Li, Ling, Hao, Hong, Liu, Wan-Quan
Format: Journal Article
Language:English
Published: SAGE PUBLICATIONS LTD 2021
Subjects:
Science & Technology
Technology
Engineering, Multidisciplinary
Instruments & Instrumentation
Engineering
Residual networks
deep learning
structural health monitoring
damage identification
uncertainties
measurement noise
DAMAGE IDENTIFICATION
NEURAL-NETWORK
Online Access:http://purl.org/au-research/grants/arc/FT190100801
http://hdl.handle.net/20.500.11937/90890

Internet

http://purl.org/au-research/grants/arc/FT190100801
http://hdl.handle.net/20.500.11937/90890

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