Dynamic response reconstruction for structural health monitoring using densely connected convolutional networks

Dynamic response reconstruction for structural health monitoring using densely connected convolutional networks

This article proposes a novel dynamic response reconstruction approach for structural health monitoring using densely connected convolutional networks. Skip connection and dense block techniques are carefully applied in the designed network architecture, which greatly facilitates the information flo...

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Bibliographic Details
Main Authors: Fan, Gao, Li, Jun, Hao, Hong
Format: Journal Article
Language:English
Published: SAGE PUBLICATIONS LTD 2021
Subjects:
Science & Technology
Technology
Engineering, Multidisciplinary
Instruments & Instrumentation
Engineering
Dynamic response reconstruction
structural health monitoring
densely connected convolutional networks
deep learning
experimental validation
MULTITYPE SENSOR PLACEMENT
DAMAGE IDENTIFICATION
NEURAL-NETWORKS
MODAL-ANALYSIS
RECOVERY
Online Access:http://purl.org/au-research/grants/arc/FT190100801
http://hdl.handle.net/20.500.11937/90889

Internet

http://purl.org/au-research/grants/arc/FT190100801
http://hdl.handle.net/20.500.11937/90889

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