A convolutional neural network‐based full‐field response reconstruction framework with multitype inputs and outputs-Reference-Cited by-同舟云学术

A convolutional neural network‐based full‐field response reconstruction framework with multitype inputs and outputs

Published:2022-03-28 Issue:7 Volume:29 Page:
ISSN:1545-2255
Container-title:Structural Control and Health Monitoring
language:en
Short-container-title:Structural Contr & Hlth

Author:

Li Yixian¹^ORCID,Ni Peng¹,Sun Limin¹²,Zhu Wang³

Affiliation:

1. Department of Bridge Engineering, College of Civil Engineering Tongji University Shanghai China

2. State Key Laboratory of Disaster Reduction in Civil Engineering, Dept. of Bridge Engineering, College of Civil Engineering Tongji University, Shanghai Qizhi Institute Shanghai China

3. Sichuan Highway Planning, Survey, Design, and Research Institute Ltd Chengdu China

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Mechanics of Materials,Building and Construction,Civil and Structural Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/stc.2961

Reference45 articles.

1. Extracting full-field dynamic strain on a wind turbine rotor subjected to arbitrary excitations using 3D point tracking and a modal expansion technique

2. O'CallahanJC.System equivalent reduction expansion process. Proc of the 7th Inter Modal Analysis Conf 19891989.

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