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

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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

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